TY - GEN
T1 - Information-theoretic attacks in the smart grid
AU - Sun, Ke
AU - Esnaola, Inaki
AU - Perlaza, Samir M.
AU - Poor, H. Vincent
N1 - Funding Information:
This research was supported in part by the European Commission under Marie Skłodowska-Curie Individual Fellowship No. 659316 and Euro-Mediterranean Cooperation ERA-NET project COM-MED. The work of H. Vincent Poor was supported in part by the U.S. National Science Foundation under Grants CMMI-1435778, CNS-1702808 and ECCS-1647198. Ke Sun acknowledges the support of China Scholarship Council (CSC).
Publisher Copyright:
© 2017 IEEE.
PY - 2018/4/17
Y1 - 2018/4/17
N2 - Gaussian random attacks that jointly minimize the amount of information obtained by the operator from the grid and the probability of attack detection are presented. The construction of the attack is posed as an optimization problem with a utility function that captures two effects: Firstly, minimizing the mutual information between the measurements and the state variables; secondly, minimizing the probability of attack detection via the Kullback-Leibler (KL) divergence between the distribution of the measurements with an attack and the distribution of the measurements without an attack. Additionally, a lower bound on the utility function achieved by the attacks constructed with imperfect knowledge of the second order statistics of the state variables is obtained. The performance of the attack construction using the sample covariance matrix of the state variables is numerically evaluated. The above results are tested in the IEEE 30-Bus test system.
AB - Gaussian random attacks that jointly minimize the amount of information obtained by the operator from the grid and the probability of attack detection are presented. The construction of the attack is posed as an optimization problem with a utility function that captures two effects: Firstly, minimizing the mutual information between the measurements and the state variables; secondly, minimizing the probability of attack detection via the Kullback-Leibler (KL) divergence between the distribution of the measurements with an attack and the distribution of the measurements without an attack. Additionally, a lower bound on the utility function achieved by the attacks constructed with imperfect knowledge of the second order statistics of the state variables is obtained. The performance of the attack construction using the sample covariance matrix of the state variables is numerically evaluated. The above results are tested in the IEEE 30-Bus test system.
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U2 - 10.1109/SmartGridComm.2017.8340708
DO - 10.1109/SmartGridComm.2017.8340708
M3 - Conference contribution
AN - SCOPUS:85050860487
T3 - 2017 IEEE International Conference on Smart Grid Communications, SmartGridComm 2017
SP - 455
EP - 460
BT - 2017 IEEE International Conference on Smart Grid Communications, SmartGridComm 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Smart Grid Communications, SmartGridComm 2017
Y2 - 23 October 2017 through 26 October 2017
ER -